MTObjects is a tool for detecting sources in astronomical images, and creating segmentation maps and parameter tables.
This is a work in progress - use at your own risk. Questions, bug reports, and suggested features are very welcome.
Python implementation by Caroline Haigh (University of Groningen).
Based on the original C implementation by Paul Teeninga et al [1]
Build instructions:
Python dependencies - pip install:
- scikit-image
- astropy
- matplotlib
- Pillow
- SciPy
- numpy
The program is written for python 3.
To recompile the C libraries, run ./recompile.sh
To get help:
python mto.py -h
To run with default parameters:
python mto.py [path/to/image.fits]
To include more faint outskirts of objects, a lower move_factor value (0.0 - 0.3) is recommended:
python mto.py [path/to/image.fits] -move_factor 0.3
Arguments:
-h, --help Show the help message and exit -out Location to save filtered image. Supports .fits and .png filenames -par_out Location to save calculated parameters. Saves in .csv format -soft_bias Constant bias to subtract from the image -gain Gain (estimated by default) -bg_mean Mean background (estimated by default) -bg_variance Background variance (estimated by default) -alpha Significance level - for the original test, this must be 1e-6 -move_factor Higher values reduce the spread of large objects. Default = 0.5 -min_distance Minimum brightness difference between objects. Default = 0.0 -verbosity Verbosity level (0-2)
We acknowledge financial support from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement No 721463 to the SUNDIAL ITN network.
[1] Citing:
@inproceedings{teeninga2015improved,
title={Improved detection of faint extended astronomical objects through statistical attribute filtering},
author={Teeninga, Paul and Moschini, Ugo and Trager, Scott C and Wilkinson, Michael HF},
booktitle={International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing},
pages={157--168},
year={2015},
organization={Springer}
}